J. Denis Sargan | |
---|---|

Born | |

Died | 13 April 1996 71) Theydon Bois, Essex, England, United Kingdom | (aged

Nationality | British |

Institution | London School of Economics |

Field | Econometrics |

Alma mater | University of Cambridge |

Doctoral students | Alok Bhargava, David Forbes Hendry, Esfandiar Maasoumi, Peter C.B. Phillips, Manuel Arellano |

**John Denis Sargan** (23 August 1924 – 13 April 1996) was a British econometrician who specialized in the analysis of economic time-series.

Sargan was born in Doncaster ^{ [1] }, Yorkshire in 1924, and was educated at Doncaster Grammar School and St John's College, Cambridge.^{ [2] } He made many contributions, notably in instrumental variables estimation, Edgeworth expansions for the distributions of econometric estimators, identification conditions in simultaneous equations models, asymptotic tests for overidentifying restrictions in homoskedastic equations and exact tests for unit roots in autoregressive and moving average models. At the LSE, Sargan was Professor of Econometrics from 1964–1984.^{ [3] } Sargan was President of the Econometric Society, a Fellow of the British Academy ^{ [4] } and an (honorary foreign) member of the American Academy of Arts and Sciences.^{ [3] }^{ [5] }

His influence on econometric methodology is evident in several fields including in the development of Generalized Method of Moments estimators.

- Sargan, J. D. (1958). "The Estimation of Economic Relationships using Instrumental Variables".
*Econometrica*.**26**(3): 393–415. doi:10.2307/1907619. JSTOR 1907619. - Sargan, J. D. (1964). "Wages and Prices in the United Kingdom: A Study in Econometric Methodology", 16, 25–54. in
*Econometric Analysis for National Economic Planning*, ed. by P. E. Hart, G. Mills, and J. N. Whittaker. London: Butterworths - Sargan, J. D. (1980). "Some Tests of Dynamic Specification for a Single Equation".
*Econometrica*.**48**(4): 879–897. doi:10.2307/1912938. JSTOR 1912938.

Published posthumously

- Sargan, J. D. (2001). "The Choice Between Sets of Regressors." Econometric Reviews 20(2).
- Sargan, J. D. (2001). "Model Building and Data Mining." Econometric Reviews 20(2): 159-170.
- Sargan, J. D. (2003). "The Development of Econometrics at LSE in the Last 30 Years." Econometric Theory 19(3): 429-438.

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In econometrics and statistics, the **generalized method of moments** (**GMM**) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable.

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**Sir David Forbes Hendry**, FBA CStat is a British econometrician, currently a professor of economics and from 2001–2007 was head of the Economics Department at the University of Oxford. He is also a professorial fellow at Nuffield College, Oxford.

The **Sargan–Hansen test** or **Sargan's test** is a statistical test used for testing over-identifying restrictions in a statistical model. It was proposed by John Denis Sargan in 1958, and several variants were derived by him in 1975. Lars Peter Hansen re-worked through the derivations and showed that it can be extended to general non-linear GMM in a time series context.

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The **Heckman correction** is a statistical technique to correct bias from non-randomly selected samples or otherwise incidentally truncated dependent variables, a pervasive issue in quantitative social sciences when using observational data. Conceptually, this is achieved by explicitly modelling the individual sampling probability of each observation together with the conditional expectation of the dependent variable. The resulting likelihood function is mathematically similar to the Tobit model for censored dependent variables, a connection first drawn by James Heckman in 1976. Heckman also developed a two-step control function approach to estimate this model, which avoids the computional burden of having to estimate both equations jointly, albeit at the cost of inefficiency. Heckman received the Nobel Memorial Prize in Economic Sciences in 2000 for his work in this field.

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A **Newey–West estimator** is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model when this model is applied in situations where the standard assumptions of regression analysis do not apply. It was devised by Whitney K. Newey and Kenneth D. West in 1987, although there are a number of later variants. The estimator is used to try to overcome autocorrelation, and heteroskedasticity in the error terms in the models, often for regressions applied to time series data. The abbreviation "HAC," sometimes used for the estimator, stands for "heteroskedasticity and autocorrelation consistent."

**Pietro Balestra** was a Swiss economist specializing in econometrics. He was born in Lugano and earned a B.A. in economics from the University of Fribourg. Balestra moved for graduate work to the University of Kansas and Stanford University. He was awarded the Ph.D. in Economics by Stanford University in 1965.

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**Whitney Kent Newey** is the Jane Berkowitz Carlton and Dennis William Carlton Professor of Economics at the Massachusetts Institute of Technology and a well-known econometrician. He is best known for developing, with Kenneth D. West, the Newey–West estimator, which robustly estimates the covariance matrix of a regression model when errors are heteroskedastic and autocorrelated.

**Manuel Arellano** is a Spanish economist specialising in econometrics and empirical microeconomics. Together with Stephen Bond, he developed the Arellano–Bond estimator, a widely used GMM estimator for panel data. This estimator is based on the earlier article by Arellano's PhD supervisor, John Denis Sargan, and Alok Bhargava. RePEc lists the paper as the most cited article in economics.

The **LSE approach to econometrics**, named for the London School of Economics, involves viewing econometric models as *reductions* from some unknown data generation process (DGP). A complex DGP is typically modelled as the starting point and this complexity allows information in the data from the real world but absent in the theory to be drawn upon. The complexity is then reduced by the econometrician by a series of restrictions which are tested.

The **Klein–Goldberger model** was an early macroeconometric model for the United States developed by Lawrence Klein and Arthur Goldberger, Klein's doctoral student at the University of Michigan, in 1955. Grounded in Keynesian macroeconomic theory, it describes the workings of the United States economy in terms of 20 simultaneous equations, using time series data from 1929 to 1952. The Klein–Goldberger model extended the pioneering work of Jan Tinbergen in the 1940s, and paved the way for even larger models such as the Wharton models of the 1960s, or the Brookings model, with almost 400 equations.

- ↑ Hendry, D. F. and P. C. B. Phillips (2017). "John Denis Sargan at the London School of Economics",
*Cowles Foundation Discussion Paper No. 2082*, Cowles Foundation for Research in Economics, Yale University, p. 1. - ↑ "SARGAN, Prof. John Denis".
*Who's Who*.*ukwhoswho.com*.**2018**(online ed.). A & C Black, an imprint of Bloomsbury Publishing plc.(subscription or UK public library membership required)(subscription required) - 1 2 https://www.independent.co.uk/news/people/obituary--professor-denis-sargan-1305657.html Obituary: Professor Denis Sargan Friday, 19 April 1996
- ↑ Hendry, David; Phillips, Peter (2003).
*John Denis Sargan 1924-1996*.*Proceedings of the British Academy*. Biographical Memoirs of Fellows II.**120**. pp. 385–409. doi:10.5871/bacad/9780197263020.003.0019. ISBN 9780197263020. - ↑ Phillips, P. C. (2003). "Vision and influence in econometrics: John Denis Sargan".
*Econometric Theory*.**19**(3): 495–512. CiteSeerX 10.1.1.193.6587 . doi:10.1017/S0266466603193085. S2CID 122949584.

- Gilbert, Christopher L. (1989). "LSE and the British Approach to Time Series Econometrics".
*Oxford Economic Papers*.**41**(1): 108–128. doi:10.1093/oxfordjournals.oep.a041887. JSTOR 2663185. - Hendry, David F. (2003). "J. Denis Sargan and the Origins of LSE Econometric Methodology".
*Econometric Theory*.**19**(3): 457–480. doi:10.1017/S0266466603193061.

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